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Scents and sensibility in agriculture: exploiting specificity in herbivore- and pathogen-induced plant volatiles for real-time crop monitoring

Periodic Reporting for period 2 - AGRISCENTS (Scents and sensibility in agriculture: exploiting specificity in herbivore- and pathogen-induced plant volatiles for real-time crop monitoring)

Reporting period: 2020-03-01 to 2021-08-31

The ERC project AGRISCENTS studies the specificity of volatile blends that plants emit in response to insect and pathogen attack, with the ultimate objective to employ sensors that detect these scents. It is envisioned that the sensors will permit real-time monitoring of the agricultural pests and diseases, enabling farmers to apply crop protection treatments at the right time and in the right place. The knowledge generated by the project and the technologies under development will drastically reduce the need for pesticides. In parallel to this project we are also developing novel formulations for the application of entomopathogenic nematodes (EPN) as biological control against insect pests. The application of EPN is usually considered too expensive and not cost effective. The combination of a robotic device that is equipped with an odor sensor and can apply EPN on plants that carry insects could be part of an ideal, cost-effective pest control strategy without any need for pesticides.
Overall, the project is well on track to reach the targets set out in the research plan. The project is divided in three interconnected work packages and each package has made considerable progress, as outlined below.

Work package 1 focusses on deciphering the plants’ odorous vocabulary to create a complete inventory of “odour-prints” for a wide range of herbivore-plant and pathogen-plant combinations. We first evaluated the efficiency of various sorbents in trapping volatile organic compounds (VOCs) with the traditional dynamic headspace volatile collection system, followed by analysis with GC-MS. With the most efficient trapping filter selected, we collected and compared the emissions induced by various plant pests and diseases. Our model plant is maize, but we are also including cotton and bean plants in some of the comparisons.

Work package 2 concerns the evaluation and optimization of sensor technologies for the detection of specific plant volatile mixtures. We are using two different approaches, one based on membrane sensors and the other on proton-transfer-reaction time-of-flight mass spectrometry (PTR-TOF-MS). We have joined as a member the MSS Forum ( which allowed us to obtain and evaluate the last generation modules of piezoresistive membrane-type surface stress sensors. In a laboratory assay, these sensors were astonishingly well at distinguishing the odorous signals from maize plants subjected to four different pests. We also purchased a state-of-the-art PTR-TOF-MS, which allows for real-time detection and quantification of volatiles blends. This machine too allows us to distinguish between the odors of plants that are under attack by different pests. Importantly, using data analyses based on deep learning we have been able to readily distinguish between healthy maize plants and maize plants with simulated caterpillar damage.

Work package 3 aims to genetically manipulate maize plants to release a unique blend of easy-to-detect volatiles (aldoximes and nitriles) upon herbivory on the roots. Well ahead of schedule, we have started to engineer gene cassettes that combine genes from poplar with inducible, root-specific promoters from maize. Using transcriptome analyses we identified two maize genes that are specifically expressed in the leaves when the roots are damaged by rootworms. In collaboration with the Max Planck Institute in Jena, Germany, the promoter fragments of the rootworm inducible maize genes, the volatile gene from poplar tree, and the terminators were step-by-step ligated into the pUC19 vector. The entire cassette of the insert fragment was isolated and cloned into the equivalent sites of the plant binary vector, pTF101.1 which enables us in a next step to transform maize plants with the Agrobacterium tumefaciens protocol.
• Demonstration that odor sensors can be used under field conditions to monitor herbivore attack of individual plants, in real-time.
• First steps towards the genetic transformation of plants to produce readily detectable volatiles when they are under attack by belowground insect pests.
• Prove-of-concept for the development of odor sensors that can be installed in robotic devices to monitor crops. The technology will provide farmers with real time information on the presence of pests and diseases in their fields.
A Spodoptera littoralis caterpillar on a maize seedling and structures of plant volatiles released